Instructions to use Jose-Ribeir/stt_Huggin_face_tech_new_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jose-Ribeir/stt_Huggin_face_tech_new_data with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="Jose-Ribeir/stt_Huggin_face_tech_new_data")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Jose-Ribeir/stt_Huggin_face_tech_new_data") model = AutoModelForQuestionAnswering.from_pretrained("Jose-Ribeir/stt_Huggin_face_tech_new_data", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- model.safetensors +1 -1
- tokenizer.json +16 -2
- training_args.bin +1 -1
model.safetensors
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tokenizer.json
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"added_tokens": [
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"version": "1.0",
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"truncation": {
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"direction": "Right",
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"max_length": 512,
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"strategy": "OnlySecond",
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"stride": 128
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"padding": {
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"strategy": {
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"Fixed": 512
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"direction": "Right",
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"pad_to_multiple_of": null,
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"pad_token": "[PAD]"
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"added_tokens": [
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training_args.bin
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oid sha256:cc979162d54729014edc387935a06ee29a331120e3f1ec66f28731b9d5340ea6
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size 4984
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